Information about how to access the Moving to Opportunity (MTO) interim evaluation data at Federal Research Data Centers (RDCs) that are run in partnership with the US Census Bureau is available here:

https://www.census.gov/about/adrm/linkage/projects/HUDmtofos.html



The attached Stata do and Matlab m files can be used to replicate the results in 

"Evidence of Neighborhood Effects from Moving to Opportunity: LATEs of Neighborhood Quality"
by Dionissi Aliprantis and Francisca G.-C. Richter

to be published in The Review of Economics and Statistics.

The following step-wise procedure reconstructs how our programs were used in estimation. 
Unfortunately, we have not been granted continued access to the MTO interim evaluation data with which we could have provided a straightforward path from running our programs to replicating the results.
However, a researcher with access to the data should be able to replicate our results after spending a a few hours with the provided files. 


STEP 1:  LINKING 2000 CENSUS AND MTO INTERIM EVALUATION DATA
-->  The file gen_nbd_quality.do constructs a measure of neighborhood quality very similar to the one we used in our paper.  The attached do file was written for the 2012-2016 ACS, and our analysis used the 2000 Census.  This measure of neighborhood quality was merged with the tracts listed in the MTO Interim Evaluation Data.

STEP 2:  OBTAINING A STARTING GUESS
-->  A starting guess for the cutpoints and the coefficients of mu_D(X) are obtained by
		MTO_estimation.m 	calling
			LL_MTO_simplest.m
			LL_MTO_simple.m
-->  A starting guess for the mu^S(X) and mu^M(X) coefficients are obtained from probits in Stata of the form 
		probit svy_cmove $X [pw= wt_totsvy] if exp==1 and
		probit svy_cmove $X [pw= wt_totsvy] if exp==2

STEP 3:  ESTIMATING THE PARAMETERS OF THE FULL MODEL
-->  The parameters of the full model are estimated by
		MTO_estimation.m 	calling
			LL_MTO2.m

STEP 4:  CONSTRUCT MODEL OUTPUT USING
-->  Various parameters are contructed in 
		MTO_postestimation.m 	

STEP 5:  ESTIMATING LATEs AND MAKING RELATED FIGURES
-->  Using the variables in estimation_results.txt contructed in 
		MTO_postestimation.m
	 create a do file doing the following:
	 	-->  Create a common support indicator variable based on mu and u_D being in the area of common support.
	 	-->  Estimate 2sls regressions, with the experimental voucher as the instrument, using just the MTO and control groups when their mu and u_D are in the area of common support.

STEP 6:  BOOTSTRAPPING 
-->  200 bootstrap replications are estimated by 
	 	MTO_BS.m 	calling
			LL_MTO2_BS.m
-->  See Appendix B for details on obtaining standard errors.

